H13-711_V3.0 HCIA-Big Data V3.0 Questions and Answers

True

False

Reduce the number of files under the same ColumnFamily in the same Region

Reduce the number of files in the same Region

Improve data read performance

Improve data writing capability

quick

skillful

spirit

light

Applied in the upper layer of Fusioninsight HD

HFS encapsulates the interface between HBase and HDFS

Provide functions such as file storage, reading, and deletion for upper-layer applications

HFS is a separate module of HBase

The amount of leaf swallowing of the entire distributed file system is limited by the throughput of a single name node

It will affect the functional implementation of the upper-level components based on HDFS

The number of objects (files, blocks) that a name node can hold is limited by the size of the memory space

Failure of this unique name node will render the entire cluster unavailable

Unified Authentication Server

Unified authentication management module

Tingyi Security Management Module

Identity information storage server

True

False

True

False

True

False

Fair

Capacity

FIFO

Mesos

Many data sources and formats

Fast data growth and fast processing

Large amount of data, large amount of calculation

Low data value density, high value

Hadoop layer

GaussDB 200

Datafarm layer

Fusiolnght Manager

True

False

TRUE

FALSE

True

False

2

3

5

4

Socket streams

JDBC

Files

Ccollections

When creating a topic, the number of replicas must not be greater than the number of currently surviving Broker instances, otherwise the topic creation will fail

When the Producer of Kafkal sends a message, it can specify which Consumer consumes the message

Kafka will store metadata information in Zookeeper for

After Kafka is installed, the sensitive data storage directory cannot be configured.

Each partition is a journal

The number of partitions is fixed

The data table can be partitioned by the value of a field

There can be further partitions or buckets under the partition

Extensibility

High reliability

high performance

Ease of use

The root of the Ldap Server directory tree generally defines the domain name the C?cin Compnitment

Ldap Server directory information is organized and stored based on a tree structure.

Each node in the Ldap Server directory tree is called an entry, and I have its own uniquely distinguishable name? ?(Plantnad? ?)

Specific objects cannot be defined under organizational units.

True

False

implementHive DDLoperate

runMap Reduce tasks

runHiveHQL tasks

all of the abovecorrect

eventual consistency

Reliablesex

wait for irrelevance

atomicity

True

False

True

False

True

False

True

False

Through big data, AI, containers, microservices, edge?Computing and other innovations?Technology,? ?

open?Support a wide range of industry ecology?combine,?combination?

?Multi-branch, multi-site, multi-industry? ?,many? ?scenarios, helping customers to distribute? ?

Support the whole network? ?,? ?, applied and managed? ?same

YARN.scheduler.capacity.root.QueueA. maximum-capacity

YARN.nodemanager.resource.cpu-vcore

YARN.nodemanager.vmem-pmom-ratio

YARN.modemanager.resource.memory-mb

Minimum queue level first

Resource recycling request queue priority

Maximum queue level first

The queue with the lowest resource utilization takes precedence

Follower synchronizes data from Leader by pulling

The master copy is called Leader, and the slave copy is called Follower

Both consumers and producers read and write data from the Leader, and can also interact directly with the Follower

Replicas are in units of partitions. Each partition has its own slave replica of the master

DataNode A

DataNode B

DataNode E

DataNode F

Single Column Value Filter

Filter List

Row Filter

Key Only Filter

A user submits a task and can use 100% of QueueA's resources.

QueueA must ensure that each user gets at least 50% of the resources.

If there are already 2 user tasks running in QueueA, then the task submitted by the third user needs to wait for the release of resources.

Each user in QueueA can only get up to 50% of the resources.

Check the Supervisori running log to determine whether the Supervisor is abnormal

View worker running logs

View the client exception stack to determine whether the client is using the problem

Check the running log of the main nimbus to determine whether the nimbus server is abnormal

End Time

processing time

Acquisition time

event time

is column oriented

is a NoSQL data

is distributed

The stored data is in the form of KV

DBService is unavailable

HDFS service unavailable

MetaStore instance unavailable

HBase service unavailable

Follower

Controller

Brocker

Leader

High malleability

High fault tolerance

High reliability

high performance

SFTP server

FTP server

Oracle Database

DB2 database

LdapServer supports TCP/P protocol.

LdapServer is a specific open source implementation based on the LDAP standard protocol.

LdapServerl uses Berkelay DB as the default backend database.

LdapServer is implemented based on OpenLDAP open source technology

Collections

JDBC

Socket streams

Files

True

False

True

False

TRUE

FALSE

delete service instance

Start and stop the service instance

Manually clear the camp

Query history monitoring

Randomly selected

Adjudicated by RegionServer

Adjudication via Zookeeper

HMaster is a dual-master mode and does not need to be adjudicated

Does not check the validity of the data

Periodically send the block-related information of this node to the NameNode

Blocks stored in different DataNodes must be different

Blocks on a DataNode. can be the same

1

2

3

4

Configure how jobs connect to external data sources

Configure how jobs connect to internal data sources

Provide optimization parameters to improve data import and export performance

Make sure there are conversion steps

DataNode

RegionServer

ResourceManager

NodeManager

001:Lily

001:Li

001:Mary, 001:Lily

001:Li, 001:Mary, 001:Lily

Non-real-time analysis. Such as log analysis, statistical analysis

data mining. Such as user behavior analysis, interest analysis, regional display

Data summary. such as clicks per user per day,Click to rank

Real-time online data analysis

robust mechanism

multiple access mechanism

HA high reliability

Metadata Persistence Mechanism

RDD has a lineage mechanism (Lineage)

RDDs are stored on disk by default

RDD is a read-only, partitionable distributed dataset

RDD is Spark's abstraction of underlying data

KDC (Key Distribution Center)

Kerberos Client

Kerberos KDC Client

Kerberos KDC Server

You can specify an instance for log collection, such as specifying a separate collection of MetaStorel logs

You can specify a time period for log collection, for example, only collect logs from 2016-1-1 to 2016-140

The node IP can be specified for log collection, for example, only the logs of a certain IP can be downloaded

A specific user can be specified for log collection, for example, only the logs generated by userA can be downloaded

Each Executor (thread) can run a number of tasks (tasks)

Each Executor (thread) can run different components (spout or bolt) of the task (task)

Each worker can run multiple Executors (threads)

Each worker can only run Executors (threads) for one topology

inheritassiknerWithPunctuateca termmarks

Inherit assigner Timestamp WithWatermark

Inherit get Current Watermark

Inherit assignerWithPeriodicWatermarks

Apply for and receive resources

Set up the running environment for the task

Allocate Container

Start a Map or Reduce task

Multi-node deployment

Statistical analysis and data mining

Security Control Based on Kerberosi Certificate

Offline and real-time data processing

True

False

True

False

TRUE

FALSE

TRUE

FALSE

When creating an external table, you need to specify the external keyword

Once the table is created, the table name cannot be changed

Once the table is created, the column names cannot be changed

Once the table is created, no new columns can be added

HDFS

Hadoop

Memory

MapReduce

YARN.nodemanager.local-dir

YARN.nodemanager.log-dirs

YARN.acl.enable

YARN.log-aggregation-enable

3

4

5

6

used to filter data

Used to optimize the performance of random reads

will increase storage consumption

Can accurately determine that a certain data does not exist

Richard Suga via YARN tasks

Check through the Loader UI interface

View through the alarm of Managerb

View through NodeManageri

Any machine -> same rack -> local resources

Any machine -> local resources -> same rack

Local resources -> same rack-＞Any machine

Same rack->any machine->local resources

put

get

list

Scan

cArbon is also a high-performance analytics engine that integrates data sources with spark.

cArbon uses a combination of lightweight compression and heavyweight compression to compress data, which can reduce data storage space by 60%-80% and greatly save hardware storage costs.

arbon is a new Apache Hadoop native file format that uses advanced columnar storage, indexing, compression, and encoding techniques to improve computational efficiency to help accelerate data queries over petabytes of magnitude, and can be used for faster interactive queries.

The purpose of using carbon is to provide ultra-fast responses to ad-hoc queries on big data.

True

False

Interceptor

Channel processor

Channel selector

None of the aboveA. True

Sink

Channel

LTopic

Source

Datastream API, DataSet API

Data batch API.DataStream API

Stream API.Batch API

Batch API, Stream API

Can start, stop and restart the service

Services can be added and uninstalled

Uncommon services can be set to hide or show

Can view the current status of the service

File

Kafka

Memory

HDFS

5

6

3

4

Memory Channel

JDBC Channel

File Channel

HDES Channel

sasl

auth

digest

world

Kafka cross-cluster data synchronization method

Kafka data backup within a single cluster

Kafka data recovery within a single cluster

None of the aboveA. True

A DataSet is a strongly typed collection of domain-specific objects

DataSet can perform most operations without deserialization

DataSet needs to be deserialized to perform operations such as sort, filter, shuffle, etC.

DataSet - highly similar to RDD. Better performance than RDD

Region

ColumnFamily

olumn

Row

One-way synchronization

two-way synchronization

Isolate out of sync

Data cross synchronization

The file data of the client is passed to the DataNode through the NameNode

Allows the client to divide the file into multiple blocks, according to DaThe address information of taNodel is entered into each DataNode in order

The client writes the entire file to each DataNodel in sequence according to the address information of the DataNode, and then divides the file into multiple blos by the DataNode)ck

The client only uploads data to one DataNode, and then the NameNodet is responsible for block replication

1

2

3

4

HFile

HLog

MemStore

HMaster